Functional multivariate Frobenius norm
Computes the functional multivariate Frobenius norm.
frobenius_norm_funct_multiv(m, PM)
m |
Data matrix with the residuals. This matrix has the same dimensions as the original data matrix. |
PM |
Penalty matrix obtained with |
Residuals are vectors. If there are p variables (columns), for every observation there is a residual that there is a p-dimensional vector. If there are n observations, the residuals are an n times p matrix.
Real number.
Irene Epifanio
Epifanio, I., Functional archetype and archetypoid analysis, 2016. Computational Statistics and Data Analysis 104, 24-34, https://doi.org/10.1016/j.csda.2016.06.007
mat <- matrix(1:400, ncol = 20) PM <- matrix(1:100, ncol = 10) frobenius_norm_funct_multiv(mat, PM)
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